Liqun Chen
Duke University
H-index: 20
North America-United States
Top articles of Liqun Chen
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning
2023
Why do we need large batchsizes in contrastive learning? a gradient-bias perspective
Advances in Neural Information Processing Systems
2022/12/6
Text feature adversarial learning for text generation with knowledge transfer from gpt2
IEEE Transactions on Neural Networks and Learning Systems
2022/10/18
Multi-modal Alignment using Representation Codebook
CVPR 2022 arXiv:2203.00048
2022/2/28
Vision-Language Pre-Training with Triple Contrastive Learning
2022
Gliding hydrodynamic modeling and identification of underwater glider based on differential evolution algorithm
Ocean engineering
2022/1/15
Simpler, faster, stronger: Breaking the log-k curse on contrastive learners with flatnce
arXiv preprint arXiv:2107.01152
2021/7/2
Spanpredict: extraction of predictive document spans with neural attention
2021/6
Contextualized perturbation for textual adversarial attack
2020/9/16
Wasserstein Contrastive Representation Distillation
2021
Proactive pseudo-intervention: Causally informed contrastive learning for interpretable vision models
arXiv preprint arXiv:2012.03369
2020/12/6
Improving text generation with student-forcing optimal transport
2020/11
Towards Robust and Efficient Contrastive Textual Representation Learning
2020/9/28
Spatiotemporal modeling for distributed parameter system under sparse sensing
Industrial & engineering chemistry research
2020/8/26
Weakly supervised cross-domain alignment with optimal transport
arXiv preprint arXiv:2008.06597
2020/8/14
Graph Optimal Transport for Cross-Domain Alignment
2020/6/26
Dynamic embedding on textual networks via a gaussian process
Proceedings of the AAAI Conference on Artificial Intelligence
2020/4/3
Sequence generation with optimal-transport-enhanced reinforcement learning
Proceedings of the AAAI Conference on Artificial Intelligence
2020/4/3
Graph-driven generative models for heterogeneous multi-task learning
Proceedings of the AAAI Conference on Artificial Intelligence
2020/4/3
Co-Authors
